LEAD: Self-Supervised Landmark Estimation by Aligning Distributions of Feature Similarity
Author:
Affiliation:
1. Indian Institute of Science,Bengaluru
2. Google Research
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9706406/9706408/09706654.pdf?arnumber=9706654
Reference55 articles.
1. Unsupervised Learning of Object Landmarks by Factorized Spatial Embeddings
2. Unsupervised learning of object frames by dense equivariant image labelling;thewlis;Advances in neural information processing systems,2017
3. Deforming Autoencoders: Unsupervised Disentangling of Shape and Appearance
4. 300 Faces in-the-Wild Challenge: The First Facial Landmark Localization Challenge
5. Spatilly consistent representation learning;roh;CVPR,2021
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1. Learning Universal Semantic Correspondences with No Supervision and Automatic Data Curation;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02
2. Learning to Predict Keypoints and Structure of Articulated Objects without Supervision;2022 26th International Conference on Pattern Recognition (ICPR);2022-08-21
3. Demystifying Unsupervised Semantic Correspondence Estimation;Lecture Notes in Computer Science;2022
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